This project seeks to develop new statistical tools for evaluating gene-environment interactions and genetic susceptibility and to apply existing statistical tools in the analysis of gene-environment studies. Methodological work has proceeded in the area of improving study designs and associated techniques for data analysis. In the past year, work has largely focused on the analysis of data from a variety of studies. Geneticists use case-parents triad designs to create an "ideal" genetic control group for studying linkage/association between variant alleles and disease. If, unbeknownst to the investigator, a population consists of distinct subpopulations with differing gene frequencies and differing baseline disease risks, associations between gene and disease arise simply by virtue of the population structure, not through any causal connection between the gene and the disease. By cleverly creating a pseudo-sibling whose genetic makeup consists of those alleles present in the parents but not transmitted to the case, geneticists are able to eliminate the effects of population structure on inferences about the risk associated with variant alleles. The advantages of case-parents triad designs in coping with unknown population structure prompted our investigation of using those designs to assess genotype-by-exposure interaction. We are continuing to investigate designs that augment case-parents triads with control-parent triads to overcome some shortcomings of using case-parents triads alone. Such designs should more fully extend protection against population structure to studies of genotype and exposure together. We are also investigating the utility of pooling DNA samples from individuals in the same or different triads to reduce cost and preserve limited samples while extracting nearly all the information available. We have also contributed to the analysis of data from studies on the effects of polymorphisms in certain DNA repair genes on bladder cancer risk and on the presence of mini- and microsatellite mutations in the children of Chernobyl cleanup workers. We have also developed a simple statistical method for assessing allelic imbalance in samples of tumor tissue.